Household Income and Investments in Child Health and Education in Ivory Coast

Denis Cogneau (DIAL, Paris School of Economics)Remi Jedwab (Paris School of Economics)

Introduction Education and child-related health demand:

role of household income → endogenous.

S = a + b x Income + e

The blindly estimated b will differ from the true coefficient b*. Solution 1: controlling variables (parental education, supply, etc.). Solution 2: IV = adequate as long as the set of instruments is uncorrelated with the error term in the main equation (or weak instruments).

Past Results Education: (i) developed countries: small positive or

nil effect (Blau 1999, Acemoglu and Pischke 2001), (ii) developing countries: high positive effect (Behrman and Knowles 1997, Cogneau and Maurin 2001)

Health: (i) developed countries: health gradient (Case, Lubotsky and Paxson 2001), (ii) developing countries: same (Duflo 2003)

Related literature: direct impact of income shocks as a result of insurance missing markets (Jacoby and Skoufias 1997, Thomas and al. 2003), impact of income volatility (Fitzsimons 2003, Kazianga 2005)

Our Natural Experiment Ivory Coast: first cocoa-producing country in the

world. Internally, fixed producer price by the state till 1998.

From the 1980s, fall in international cocoa prices. 1990: first diminution of the national cocoa producer price in 25 years. 1994 and 1997: increase of the same price.

Conclusion: exogenous strong decrease in the income of cocoa households vs. non-cocoa households → differential impact on investments in human capital.

Outcomes: school attendance 5-17 yo, health status 0-18 yo and anthropometric status 0-5 yo.

Our Natural Experiment

Data: cross-section 1985-1988 (CILSS), 1993 and 1998 (EP)

1985 1990 1994 1997

National fixed producer price

1993 19981988

year

survey wave

DiD-IV Strategy

Cocoa households more “affected” than non-cocoa households → relatively less income in 1993 vs. 1988 → relatively less education and health for their children (conversely for 1993-1998)

Econometric specification: instrument income with “belonging to a cocoa-producing household in 1993/1998 vs. 1988” (difference-in-difference with a treatment group and a control group). Other examples of DiD-IV: Duflo 2000, Chen 2004.

Econometric model

For child i in household h in village v at time t:

Western and Eastern Forests: main cocoa regions

Limitation 1: non-parallel trends?

Since we control for “belonging to cocoa-producing household”, a bias is allowed between cocoa and non-cocoa households.

However, better if rather similar. Guarantees that non-cocoa households would have equally modified their human capital investments decisions if they had faced the same income shock that cocoa households. Control group = non-cocoa farmers.

Many tests available.

1) T-tests on observable general characteristics 1988

2) T-tests on observable specific characteristics 1988

Once we regress active/abandon/number of inactive days due to illness on “belonging to a cocoa household” + village-time fixed effects, cocoa is non-significant.

Same height-for-age Z-score kernel distribution in both groups 1988

Limitation 2: change in supply?

Supply (quality of schools and health centers) is likely to change more in cocoa-dominant villages, since aggregate income is relatively lower there.

Always inclusion of village-time fixed effects.

Limitation 3: geographical migration?

E.g.: problematical if differential migration (between both groups) from “forest” regions to other regions due to the negative shock 1990-1993.

Limitation 4: professional migration?

E.g.: problematical if some cocoa households have switched to non-cocoa production due to the negative shock 1990-1993. Irreversibility story: cocoa trees only mature after 5-10 years.

Econometric model

For child i in household h in village v at time t:

Limitation 5: other consequential changes than income?

E.g.: problematical if the fall of cocoa prices alters cocoa-specific anticipated returns to education or borrowing constraints?

This is very unlikely. Returns to education are presumably unrelated to opportunities in agriculture. Borrowing constraints do not depend upon producer prices or income, but assets and social capital (unchanged in the short term).

Any change in schooling is thus only attributable to changes in income!

Econometric model

For child i in household h in village v at time t:

Econometric Results

1. School Attendance

2. Health Status

3. Anthropometric Status

School Attendance:School Attendance:

Linear probability model.

Controls: dummies equal 1 if the household chef is a woman, literate, has achieved primary schooling, has spent at least one year in secondary schooling, has obtained the BEPC (at the end of secondary schooling), has obtained the BAC or more (at the end or after high school), dummies equal 1 if the household owns livestock, a business, has a household member being a civil servant, the ratio of extended family over household size and the share of women in the household.

Obs. 5-17, All: 18992. Obs. 5-11, All: 11782. Obs. 5-17, Forest: 9111. Obs. 5-17, Forest: 5802.

Children 0-18

Health Status:Health Status:

Linear probability model.

Controls: dummies equal 1 if the household chef is literate, has achieved primary schooling, has spent at least one year in secondary schooling, has obtained the BEPC (at the end of secondary schooling), has obtained the BAC or more (at the end or after high school), dummies equal 1 if the household owns livestock, a business, has a household member being a civil servant, and the share of women in the household.

Obs. All: 28002. Obs. Forest: 13681.

Anthropometric Status:Anthropometric Status:

Controls: dummies equal 1 if the household chef is literate, has achieved primary schooling, has spent at least one year in secondary schooling, has obtained the BEPC (at the end of secondary schooling), has obtained the BAC or more (at the end or after high school), dummies equal 1 if the household owns livestock, a business, has a household member being a civil servant, or belongs to a certain ethnical group (Akan, Krou, Mande, Voltaque, Other, Foreigner), and the �shareof women in the household.

Obs. 0-5, Forest: 2824. Obs. 3-5, Forest: 1434.

Conclusion A 10% increase in parental income: (a) a 2.3 - 3 point

increase in the likelihood to attend school for 5-17 year-old children, (b) a 6 point decrease in the likelihood that a 3-5 year-old child is malnourished, and (c) a 1.8 - 2 point reduction in the probability that a 0-18 year-old child is sick.

Our contribution: (1) OLS are downward biased in LDC, robust to within and not due to weak instruments. Why (given that theoretical models emphasize an upward ability bias)? (i) Simultaneity (ii) Measurement error (iii) Omission bias. (2) Imperfect credit and insurance markets. (3) One of the first papers to empirically address child-related health demand.